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Plant input-mapping-based predictive control of systems through band-limited networks

机译:通过带限网络对工厂进行基于输入映射的系统预测控制

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摘要

A new control method for network-based control systems, with guaranteed closed-loop stability, is proposed. The method substantially enhances the conventional networked model-based predictive control (NMBPC) schemes. In conventional NMBPC methods, associated with a pre-specified range of possible time delays, a vector of stabilising control signals is determined and transmitted to the plant side of the network, where, based on the actually occurred time delay, just one entry of the control vector is selected and applied to the plant. In practice, stability issues may arise when the network time delay is not small enough. A modified method, using the plant-input mapping (PIM) discretisation technique, with the possibility of guaranteeing the closed-loop stability is introduced. In order to alleviate the deficiency of some existing transfer function-based methods, which implicitly assume a non-realistic zero initial condition at the outset of every sampling instant, a state-space representation is proposed. Simulation studies on well-known benchmark problems demonstrate the effectiveness of the proposed PIM-based NMBPC method.
机译:提出了一种具有闭环稳定性的基于网络的控制系统控制新方法。该方法大大增强了传统的基于网络模型的预测控制(NMBPC)方案。在常规的NMBPC方法中,与可能的时间延迟的预定范围相关联,确定稳定控制信号的向量并将其传输到网络的工厂侧,在网络中,根据实际发生的时间延迟,仅输入一个选择控制载体并将其应用于植物。实际上,当网络时间延迟不够小时,可能会出现稳定性问题。介绍了一种使用工厂输入映射(PIM)离散化技术的改进方法,该方法可以保证闭环稳定性。为了缓解一些现有的基于传递函数的方法的不足,该方法在每个采样时刻的开始就隐式地假设了一个不现实的零初始条件,提出了一种状态空间表示法。对著名基准问题的仿真研究证明了所提出的基于PIM的NMBPC方法的有效性。

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